Using Surveys to Examine the Association of Exposure to ML Mortality Risk Predictions With Medical Oncologists' Prognostic Accuracy and Decision-making

The study consisted of a 3 × 3 online factorial experiment employing a survey instrument hosted via Qualtrics presenting describing three patient vignettes. The three patient vignettes varied by various clinical characteristics including age, gender, performance status, smoking history, extent of disease, symptoms and molecular status. Each patient had advanced non-small cell lung cancer (aNSCLC). Each vignette had two parts: Part 1 described the case history for one of the three patients, after which prognostic estimates and medical decision-making was assessed (i.e. 1, 2, 3). Part 2 immediately followed and described the same vignette from the same patient with added information from a hypothetical ML predictive algorithm (i.e. A, B, C). The order of the vignettes in each survey was randomized with regard to presentation strategies for the ML risk predictions, so that there were 6 versions of the survey to which each participant was randomized.